Overview

Dataset statistics

Number of variables19
Number of observations2406
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory359.5 KiB
Average record size in memory153.0 B

Variable types

DateTime1
TimeSeries15
Boolean1
Numeric2

Timeseries statistics

Number of series15
Time series length2406
Starting point2010-01-26 00:00:00
Ending point2019-08-19 00:00:00
Period1 day, 10 hours and 50 minutes
2026-02-01T22:32:51.455872image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:51.742552image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Alerts

repaired? has constant value "False"Constant
AD is highly overall correlated with OBVHigh correlation
ATR is highly overall correlated with NATR and 1 other fieldsHigh correlation
CMO is highly overall correlated with MFI and 2 other fieldsHigh correlation
EMA is highly overall correlated with KAMA and 6 other fieldsHigh correlation
KAMA is highly overall correlated with EMA and 6 other fieldsHigh correlation
MA is highly overall correlated with EMA and 6 other fieldsHigh correlation
MFI is highly overall correlated with CMO and 2 other fieldsHigh correlation
MidPrice is highly overall correlated with EMA and 6 other fieldsHigh correlation
NATR is highly overall correlated with ATR and 7 other fieldsHigh correlation
OBV is highly overall correlated with ADHigh correlation
ROC is highly overall correlated with CMO and 2 other fieldsHigh correlation
TRANGE is highly overall correlated with ATRHigh correlation
TSF is highly overall correlated with EMA and 6 other fieldsHigh correlation
WILLR is highly overall correlated with CMO and 2 other fieldsHigh correlation
WMA is highly overall correlated with EMA and 6 other fieldsHigh correlation
close is highly overall correlated with EMA and 6 other fieldsHigh correlation
close is non stationaryNon stationary
MA is non stationaryNon stationary
EMA is non stationaryNon stationary
KAMA is non stationaryNon stationary
WMA is non stationaryNon stationary
MidPrice is non stationaryNon stationary
AD is non stationaryNon stationary
OBV is non stationaryNon stationary
NATR is non stationaryNon stationary
TSF is non stationaryNon stationary
close is seasonalSeasonal
MA is seasonalSeasonal
EMA is seasonalSeasonal
KAMA is seasonalSeasonal
WMA is seasonalSeasonal
MidPrice is seasonalSeasonal
AD is seasonalSeasonal
OBV is seasonalSeasonal
NATR is seasonalSeasonal
Date has unique valuesUnique
EMA has unique valuesUnique
KAMA has unique valuesUnique
NATR has unique valuesUnique
ATR has unique valuesUnique
BOP has 796 (33.1%) zerosZeros
ROC has 241 (10.0%) zerosZeros
WILLR has 241 (10.0%) zerosZeros
TRANGE has 40 (1.7%) zerosZeros

Reproduction

Analysis started2026-02-02 04:32:32.809485
Analysis finished2026-02-02 04:32:51.100054
Duration18.29 seconds
Software versionydata-profiling vv4.18.1
Download configurationconfig.json

Variables

Date
Date

Unique 

Distinct2406
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size37.6 KiB
Minimum2010-01-26 00:00:00
Maximum2019-08-19 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-02-01T22:32:51.915991image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:51.995237image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

close
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct89
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.075229
Minimum26
Maximum114
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:32:52.095264image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum26
5-th percentile42
Q152
median74
Q394
95-th percentile105
Maximum114
Range88
Interquartile range (IQR)42

Descriptive statistics

Standard deviation22.145046
Coefficient of variation (CV)0.3030445
Kurtosis-1.3929754
Mean73.075229
Median Absolute Deviation (MAD)21
Skewness-0.029287288
Sum175819
Variance490.40307
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.6171947491
2026-02-01T22:32:52.182318image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:32:52.382993image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 47.03 seconds
2026-02-01T22:32:53.132537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
9767
 
2.8%
4665
 
2.7%
4964
 
2.7%
9362
 
2.6%
4862
 
2.6%
5359
 
2.5%
5059
 
2.5%
4556
 
2.3%
9452
 
2.2%
5252
 
2.2%
Other values (79)1808
75.1%
ValueCountFrequency (%)
261
 
< 0.1%
272
 
0.1%
282
 
0.1%
293
0.1%
307
0.3%
317
0.3%
327
0.3%
335
0.2%
344
0.2%
355
0.2%
ValueCountFrequency (%)
1142
 
0.1%
1133
 
0.1%
1123
 
0.1%
1113
 
0.1%
1106
 
0.2%
1098
 
0.3%
10815
0.6%
10732
1.3%
10626
1.1%
10529
1.2%
2026-02-01T22:32:52.255021image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

repaired?
Boolean

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.1 KiB
False
2406 
ValueCountFrequency (%)
False2406
100.0%
2026-02-01T22:32:53.448125image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

MA
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct704
Distinct (%)29.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.116126
Minimum29.2
Maximum112.1
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:32:53.500265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum29.2
5-th percentile42.125
Q151.725
median73.8
Q394.275
95-th percentile104.7
Maximum112.1
Range82.9
Interquartile range (IQR)42.55

Descriptive statistics

Standard deviation22.065765
Coefficient of variation (CV)0.30179068
Kurtosis-1.4055755
Mean73.116126
Median Absolute Deviation (MAD)21.2
Skewness-0.037423164
Sum175917.4
Variance486.89799
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.4836075885
2026-02-01T22:32:53.563877image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:32:53.741320image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 47.03 seconds
2026-02-01T22:32:54.428250image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
45.618
 
0.7%
53.712
 
0.5%
69.110
 
0.4%
48.610
 
0.4%
56.510
 
0.4%
51.610
 
0.4%
8610
 
0.4%
53.210
 
0.4%
96.710
 
0.4%
96.910
 
0.4%
Other values (694)2296
95.4%
ValueCountFrequency (%)
29.22
0.1%
29.43
0.1%
29.51
 
< 0.1%
29.71
 
< 0.1%
29.83
0.1%
301
 
< 0.1%
30.11
 
< 0.1%
30.22
0.1%
30.31
 
< 0.1%
30.41
 
< 0.1%
ValueCountFrequency (%)
112.11
< 0.1%
1121
< 0.1%
111.61
< 0.1%
111.21
< 0.1%
1111
< 0.1%
110.61
< 0.1%
1101
< 0.1%
109.51
< 0.1%
109.31
< 0.1%
109.21
< 0.1%
2026-02-01T22:32:53.620533image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

EMA
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2406
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.118275
Minimum29.180863
Maximum112.04341
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:32:54.918536image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum29.180863
5-th percentile42.330028
Q151.690822
median73.850823
Q394.331743
95-th percentile104.55472
Maximum112.04341
Range82.862548
Interquartile range (IQR)42.640921

Descriptive statistics

Standard deviation22.033046
Coefficient of variation (CV)0.30133432
Kurtosis-1.4122312
Mean73.118275
Median Absolute Deviation (MAD)21.118924
Skewness-0.038883189
Sum175922.57
Variance485.4551
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.5894762534
2026-02-01T22:32:54.988199image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:32:55.161693image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 47.03 seconds
2026-02-01T22:32:55.702770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
77.530569591
 
< 0.1%
76.888647851
 
< 0.1%
76.363439151
 
< 0.1%
75.751904761
 
< 0.1%
75.433376621
 
< 0.1%
75.718217241
 
< 0.1%
75.951268651
 
< 0.1%
75.414674351
 
< 0.1%
74.612006281
 
< 0.1%
74.137096051
 
< 0.1%
Other values (2396)2396
99.6%
ValueCountFrequency (%)
29.180862781
< 0.1%
29.221054511
< 0.1%
29.270177731
< 0.1%
29.5116151
< 0.1%
29.782230451
< 0.1%
29.821824921
< 0.1%
29.996883891
< 0.1%
30.036038571
< 0.1%
30.388743891
< 0.1%
30.393122471
< 0.1%
ValueCountFrequency (%)
112.0434111
< 0.1%
111.85369991
< 0.1%
111.60861351
< 0.1%
111.33484541
< 0.1%
111.07719421
< 0.1%
110.64990411
< 0.1%
110.12766051
< 0.1%
109.71158511
< 0.1%
109.27396441
< 0.1%
109.20304841
< 0.1%
2026-02-01T22:32:55.043675image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

KAMA
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2406
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean72.876204
Minimum28.95192
Maximum110.3248
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:32:56.267072image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum28.95192
5-th percentile41.767189
Q151.420175
median73.595862
Q394.557748
95-th percentile104.9213
Maximum110.3248
Range81.372876
Interquartile range (IQR)43.137573

Descriptive statistics

Standard deviation22.157334
Coefficient of variation (CV)0.30404073
Kurtosis-1.3929516
Mean72.876204
Median Absolute Deviation (MAD)21.570002
Skewness-0.031650425
Sum175340.15
Variance490.94744
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.592345465
2026-02-01T22:32:56.368001image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:32:56.632947image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 47.03 seconds
2026-02-01T22:32:57.268978image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
75.862342551
 
< 0.1%
75.333558481
 
< 0.1%
74.978312931
 
< 0.1%
74.451311781
 
< 0.1%
74.390990771
 
< 0.1%
74.480232221
 
< 0.1%
74.523752831
 
< 0.1%
74.444027741
 
< 0.1%
74.201745451
 
< 0.1%
74.110589561
 
< 0.1%
Other values (2396)2396
99.6%
ValueCountFrequency (%)
28.951920411
< 0.1%
28.955302741
< 0.1%
28.957153281
< 0.1%
28.98224861
< 0.1%
28.985205321
< 0.1%
29.010945571
< 0.1%
29.037831651
< 0.1%
29.045998841
< 0.1%
29.056594641
< 0.1%
29.092752861
< 0.1%
ValueCountFrequency (%)
110.32479661
< 0.1%
110.3059551
< 0.1%
110.2553551
< 0.1%
109.87023491
< 0.1%
109.23310581
< 0.1%
108.65195941
< 0.1%
108.18039491
< 0.1%
107.87786461
< 0.1%
107.79571361
< 0.1%
107.7564351
< 0.1%
2026-02-01T22:32:56.454759image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

WMA
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct1737
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.10164
Minimum28.727273
Maximum112.67273
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:32:57.618263image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum28.727273
5-th percentile42.122727
Q151.763636
median73.654545
Q394.25
95-th percentile104.77727
Maximum112.67273
Range83.945455
Interquartile range (IQR)42.486364

Descriptive statistics

Standard deviation22.080988
Coefficient of variation (CV)0.30205872
Kurtosis-1.4040969
Mean73.10164
Median Absolute Deviation (MAD)21.209091
Skewness-0.035218322
Sum175882.55
Variance487.57003
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.5598439405
2026-02-01T22:32:57.685866image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:32:58.092441image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 47.03 seconds
2026-02-01T22:32:58.822702image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
52.65
 
0.2%
96.072727275
 
0.2%
45.309090915
 
0.2%
96.909090914
 
0.2%
93.290909094
 
0.2%
102.34545454
 
0.2%
96.981818184
 
0.2%
97.418181824
 
0.2%
56.254545454
 
0.2%
47.018181824
 
0.2%
Other values (1727)2363
98.2%
ValueCountFrequency (%)
28.727272731
< 0.1%
28.854545451
< 0.1%
29.018181821
< 0.1%
29.072727271
< 0.1%
29.290909091
< 0.1%
29.41
< 0.1%
29.418181821
< 0.1%
29.527272731
< 0.1%
29.727272732
0.1%
29.745454551
< 0.1%
ValueCountFrequency (%)
112.67272731
< 0.1%
112.56363641
< 0.1%
112.16363641
< 0.1%
112.01818181
< 0.1%
111.54545451
< 0.1%
1111
< 0.1%
110.32727271
< 0.1%
109.81818181
< 0.1%
109.81
< 0.1%
109.34545451
< 0.1%
2026-02-01T22:32:57.923017image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

MidPrice
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct163
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.023691
Minimum29
Maximum111.5
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:32:59.167454image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum29
5-th percentile42.125
Q152
median74
Q394.5
95-th percentile105
Maximum111.5
Range82.5
Interquartile range (IQR)42.5

Descriptive statistics

Standard deviation22.001976
Coefficient of variation (CV)0.30129916
Kurtosis-1.4027917
Mean73.023691
Median Absolute Deviation (MAD)21
Skewness-0.036822895
Sum175695
Variance484.08696
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.523185574
2026-02-01T22:32:59.236578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:32:59.629584image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 47.03 seconds
2026-02-01T22:33:00.334523image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
45.554
 
2.2%
47.554
 
2.2%
48.544
 
1.8%
50.539
 
1.6%
9538
 
1.6%
9636
 
1.5%
52.536
 
1.5%
94.535
 
1.5%
4733
 
1.4%
4932
 
1.3%
Other values (153)2005
83.3%
ValueCountFrequency (%)
292
 
0.1%
29.53
 
0.1%
3010
0.4%
30.54
 
0.2%
313
 
0.1%
31.52
 
0.1%
327
0.3%
32.52
 
0.1%
33.51
 
< 0.1%
343
 
0.1%
ValueCountFrequency (%)
111.51
 
< 0.1%
110.52
 
0.1%
1102
 
0.1%
1099
 
0.4%
108.51
 
< 0.1%
10817
0.7%
107.510
 
0.4%
1071
 
< 0.1%
106.514
0.6%
10628
1.2%
2026-02-01T22:32:59.458203image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

BOP
Real number (ℝ)

Zeros 

Distinct28
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0086177054
Minimum-1
Maximum1
Zeros796
Zeros (%)33.1%
Negative798
Negative (%)33.2%
Memory size37.6 KiB
2026-02-01T22:33:00.655569image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-0.5
median0
Q30.5
95-th percentile1
Maximum1
Range2
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.62520657
Coefficient of variation (CV)72.549077
Kurtosis-0.90555891
Mean0.0086177054
Median Absolute Deviation (MAD)0.5
Skewness0.0085586304
Sum20.734199
Variance0.39088326
MonotonicityNot monotonic
2026-02-01T22:33:00.705300image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0796
33.1%
1361
15.0%
-1323
13.4%
0.5272
 
11.3%
-0.5267
 
11.1%
-0.666666666787
 
3.6%
0.666666666777
 
3.2%
-0.333333333371
 
3.0%
0.333333333367
 
2.8%
-0.7517
 
0.7%
Other values (18)68
 
2.8%
ValueCountFrequency (%)
-1323
13.4%
-0.85714285711
 
< 0.1%
-0.83333333333
 
0.1%
-0.81818181821
 
< 0.1%
-0.84
 
0.2%
-0.7517
 
0.7%
-0.71428571432
 
0.1%
-0.666666666787
 
3.6%
-0.68
 
0.3%
-0.5267
11.1%
ValueCountFrequency (%)
1361
15.0%
0.83333333331
 
< 0.1%
0.88
 
0.3%
0.758
 
0.3%
0.666666666777
 
3.2%
0.62
 
0.1%
0.5272
11.3%
0.44
 
0.2%
0.333333333367
 
2.8%
0.259
 
0.4%

CMO
Numeric time series

High correlation 

Distinct2112
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.33900862
Minimum-82.186172
Maximum77.472089
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:33:00.907087image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-82.186172
5-th percentile-52.613881
Q1-20.24712
median2.8245097
Q322.478729
95-th percentile46.419461
Maximum77.472089
Range159.65826
Interquartile range (IQR)42.725849

Descriptive statistics

Standard deviation30.233525
Coefficient of variation (CV)89.182173
Kurtosis-0.48262315
Mean0.33900862
Median Absolute Deviation (MAD)21.34906
Skewness-0.2417927
Sum815.65474
Variance914.06606
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value1.637694919 × 10-18
2026-02-01T22:33:01.011084image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:01.263822image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 47.03 seconds
2026-02-01T22:33:01.927545image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
61.685302055
 
0.2%
73.443061524
 
0.2%
45.913145614
 
0.2%
32.06649274
 
0.2%
11.426639774
 
0.2%
19.24352424
 
0.2%
34.038509913
 
0.1%
39.563096053
 
0.1%
31.576209833
 
0.1%
40.85394663
 
0.1%
Other values (2102)2369
98.5%
ValueCountFrequency (%)
-82.186172113
0.1%
-82.186172111
 
< 0.1%
-75.353174161
 
< 0.1%
-75.353174162
0.1%
-75.242503951
 
< 0.1%
-74.662473581
 
< 0.1%
-73.850394661
 
< 0.1%
-73.576753911
 
< 0.1%
-72.685969541
 
< 0.1%
-72.629569561
 
< 0.1%
ValueCountFrequency (%)
77.472089091
 
< 0.1%
73.443061522
0.1%
73.443061524
0.2%
72.868941281
 
< 0.1%
72.864482061
 
< 0.1%
72.864482061
 
< 0.1%
67.645124621
 
< 0.1%
66.707419681
 
< 0.1%
66.004363571
 
< 0.1%
66.004363571
 
< 0.1%
2026-02-01T22:33:01.097023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

MFI
Numeric time series

High correlation 

Distinct2356
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.393243
Minimum-4.9790265 × 10-15
Maximum98.154262
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:33:02.544325image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-4.9790265 × 10-15
5-th percentile19.835225
Q137.776658
median51.428515
Q363.32268
95-th percentile78.135626
Maximum98.154262
Range98.154262
Interquartile range (IQR)25.546022

Descriptive statistics

Standard deviation17.838792
Coefficient of variation (CV)0.35399174
Kurtosis-0.4317062
Mean50.393243
Median Absolute Deviation (MAD)12.844013
Skewness-0.15051564
Sum121246.14
Variance318.22249
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value7.682541842 × 10-14
2026-02-01T22:33:02.668875image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:02.998093image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 47.03 seconds
2026-02-01T22:33:03.849778image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
71.331646913
 
0.1%
47.017172913
 
0.1%
70.201301192
 
0.1%
22.033551722
 
0.1%
33.105658862
 
0.1%
34.332731792
 
0.1%
61.711320492
 
0.1%
35.303079662
 
0.1%
49.718386852
 
0.1%
75.777331952
 
0.1%
Other values (2346)2384
99.1%
ValueCountFrequency (%)
-4.979026481 × 10-151
< 0.1%
-4.829293211 × 10-151
< 0.1%
-4.725228247 × 10-151
< 0.1%
2.9908652431
< 0.1%
5.0527226551
< 0.1%
5.0983662041
< 0.1%
5.1599709981
< 0.1%
6.2717748351
< 0.1%
6.9792264661
< 0.1%
7.1543500941
< 0.1%
ValueCountFrequency (%)
98.154261861
< 0.1%
97.951501121
< 0.1%
97.586131531
< 0.1%
97.579073761
< 0.1%
97.513929751
< 0.1%
97.494480531
< 0.1%
94.335396181
< 0.1%
94.285922451
< 0.1%
94.23076921
< 0.1%
93.443801661
< 0.1%
2026-02-01T22:33:02.798102image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

ROC
Numeric time series

High correlation  Zeros 

Distinct722
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.050252806
Minimum-25
Maximum26.923077
Zeros241
Zeros (%)10.0%
Memory size37.6 KiB
2026-02-01T22:33:04.330993image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-25
5-th percentile-10.702381
Q1-3.8834951
median0
Q33.8834951
95-th percentile9.8453466
Maximum26.923077
Range51.923077
Interquartile range (IQR)7.7669903

Descriptive statistics

Standard deviation6.3265269
Coefficient of variation (CV)125.894
Kurtosis0.86026576
Mean0.050252806
Median Absolute Deviation (MAD)3.8834951
Skewness-0.082271332
Sum120.90825
Variance40.024942
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value2.048649555 × 10-11
2026-02-01T22:33:04.669338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:04.915370image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 47.03 seconds
2026-02-01T22:33:05.657837image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
0241
 
10.0%
6.66666666719
 
0.8%
-2.04081632718
 
0.7%
2.04081632717
 
0.7%
3.22580645216
 
0.7%
415
 
0.6%
-3.12515
 
0.6%
4.16666666714
 
0.6%
3.84615384614
 
0.6%
213
 
0.5%
Other values (712)2024
84.1%
ValueCountFrequency (%)
-251
< 0.1%
-24.324324321
< 0.1%
-21.621621621
< 0.1%
-21.212121211
< 0.1%
-21.052631581
< 0.1%
-211
< 0.1%
-19.402985071
< 0.1%
-18.918918922
0.1%
-18.840579711
< 0.1%
-18.604651161
< 0.1%
ValueCountFrequency (%)
26.923076921
< 0.1%
22.580645161
< 0.1%
22.222222221
< 0.1%
22.093023261
< 0.1%
21.428571431
< 0.1%
21.052631581
< 0.1%
20.930232562
0.1%
202
0.1%
18.751
< 0.1%
18.518518521
< 0.1%
2026-02-01T22:33:04.750760image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

WILLR
Numeric time series

High correlation  Zeros 

Distinct98
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-47.653861
Minimum-100
Maximum-0
Zeros241
Zeros (%)10.0%
Memory size37.6 KiB
2026-02-01T22:33:06.259472image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-100
5-th percentile-100
Q1-77.777778
median-44.444444
Q3-20
95-th percentile-0
Maximum-0
Range100
Interquartile range (IQR)57.777778

Descriptive statistics

Standard deviation31.869818
Coefficient of variation (CV)-0.66877724
Kurtosis-1.3176014
Mean-47.653861
Median Absolute Deviation (MAD)27.777778
Skewness-0.1003409
Sum-114655.19
Variance1015.6853
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value1.905522187 × 10-16
2026-02-01T22:33:06.358669image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:06.600887image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 47.03 seconds
2026-02-01T22:33:07.294559image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
-0241
 
10.0%
-50154
 
6.4%
-100138
 
5.7%
-33.33333333128
 
5.3%
-25123
 
5.1%
-20111
 
4.6%
-16.6666666792
 
3.8%
-66.6666666791
 
3.8%
-7588
 
3.7%
-83.3333333386
 
3.6%
Other values (88)1154
48.0%
ValueCountFrequency (%)
-100138
5.7%
-10032
 
1.3%
-95.454545451
 
< 0.1%
-95.238095241
 
< 0.1%
-951
 
< 0.1%
-94.736842111
 
< 0.1%
-94.444444442
 
0.1%
-93.751
 
< 0.1%
-93.333333332
 
0.1%
-92.857142867
 
0.3%
ValueCountFrequency (%)
-0241
10.0%
-4.7619047621
 
< 0.1%
-5.2631578952
 
0.1%
-6.6666666671
 
< 0.1%
-7.1428571433
 
0.1%
-7.6923076925
 
0.2%
-8.3333333339
 
0.4%
-8.6956521742
 
0.1%
-9.09090909126
 
1.1%
-1017
 
0.7%
2026-02-01T22:33:06.437422image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

AD
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct1806
Distinct (%)75.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21015809
Minimum893132.13
Maximum42828772
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:33:07.777269image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum893132.13
5-th percentile5836173.2
Q115452368
median22456171
Q325559616
95-th percentile36272473
Maximum42828772
Range41935640
Interquartile range (IQR)10107248

Descriptive statistics

Standard deviation8594702.4
Coefficient of variation (CV)0.40896367
Kurtosis-0.15419048
Mean21015809
Median Absolute Deviation (MAD)5288976.7
Skewness0.048496395
Sum5.0564037 × 1010
Variance7.386891 × 1013
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.7328372764
2026-02-01T22:33:07.869161image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:08.117691image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 47.03 seconds
2026-02-01T22:33:08.765670image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
25287507.517
 
0.3%
30566385.286
 
0.2%
14176422.586
 
0.2%
5797574.296
 
0.2%
18901673.286
 
0.2%
14815340.585
 
0.2%
5930001.295
 
0.2%
33029610.285
 
0.2%
25755212.185
 
0.2%
15924649.245
 
0.2%
Other values (1796)2350
97.7%
ValueCountFrequency (%)
893132.13331
< 0.1%
1191203.1331
< 0.1%
1238770.1331
< 0.1%
1256938.6672
0.1%
14380931
< 0.1%
1505538.3331
< 0.1%
1530563.3331
< 0.1%
1549849.6671
< 0.1%
1668615.1331
< 0.1%
1896832.3331
< 0.1%
ValueCountFrequency (%)
42828772.441
< 0.1%
42770737.611
< 0.1%
42554935.612
0.1%
42475559.611
< 0.1%
42225058.611
< 0.1%
42141626.441
< 0.1%
42054419.111
< 0.1%
42047934.441
< 0.1%
42000639.441
< 0.1%
41969051.442
0.1%
2026-02-01T22:33:07.949150image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

OBV
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct1628
Distinct (%)67.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1938878.3
Minimum-11281501
Maximum17239093
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:33:09.346744image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-11281501
5-th percentile-5843366.2
Q1-1821070.8
median1162726
Q33644599
95-th percentile13371821
Maximum17239093
Range28520594
Interquartile range (IQR)5465669.8

Descriptive statistics

Standard deviation5590567.6
Coefficient of variation (CV)2.8834031
Kurtosis0.094304167
Mean1938878.3
Median Absolute Deviation (MAD)2720577
Skewness0.69695817
Sum4.6649411 × 109
Variance3.1254446 × 1013
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.7567319259
2026-02-01T22:33:09.445888image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:09.691654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 47.03 seconds
2026-02-01T22:33:10.337488image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
124553108
 
0.3%
-17871197
 
0.3%
46104507
 
0.3%
17523186
 
0.2%
10310136
 
0.2%
22672746
 
0.2%
102007396
 
0.2%
-29804356
 
0.2%
-24424346
 
0.2%
94994446
 
0.2%
Other values (1618)2342
97.3%
ValueCountFrequency (%)
-112815011
< 0.1%
-109155751
< 0.1%
-106063442
0.1%
-104855361
< 0.1%
-102463222
0.1%
-102255361
< 0.1%
-102215351
< 0.1%
-101918541
< 0.1%
-101309071
< 0.1%
-100375101
< 0.1%
ValueCountFrequency (%)
172390931
 
< 0.1%
172337273
0.1%
166307261
 
< 0.1%
165168772
0.1%
164785892
0.1%
164702003
0.1%
162839663
0.1%
159227311
 
< 0.1%
157792071
 
< 0.1%
157339201
 
< 0.1%
2026-02-01T22:33:09.524143image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

NATR
Numeric time series

High correlation  Non stationary  Seasonal  Unique 

Distinct2406
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.9055739
Minimum0.99195246
Maximum7.9900552
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:33:10.690603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.99195246
5-th percentile1.5516377
Q12.1204332
median2.6458587
Q33.5069273
95-th percentile5.1340899
Maximum7.9900552
Range6.9981027
Interquartile range (IQR)1.3864941

Descriptive statistics

Standard deviation1.1142117
Coefficient of variation (CV)0.38347389
Kurtosis1.8321109
Mean2.9055739
Median Absolute Deviation (MAD)0.60759023
Skewness1.2328214
Sum6990.8108
Variance1.2414678
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.0102408407
2026-02-01T22:33:11.054282image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:11.310933image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 47.03 seconds
2026-02-01T22:33:12.025754image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
2.3061224491
 
< 0.1%
2.363387441
 
< 0.1%
2.2910991481
 
< 0.1%
2.4501344231
 
< 0.1%
2.5339551811
 
< 0.1%
2.5395778141
 
< 0.1%
2.4509437781
 
< 0.1%
2.889818711
 
< 0.1%
3.1614063941
 
< 0.1%
2.9940258941
 
< 0.1%
Other values (2396)2396
99.6%
ValueCountFrequency (%)
0.99195245711
< 0.1%
0.99681149781
< 0.1%
1.0039453161
< 0.1%
1.0552564221
< 0.1%
1.0687376711
< 0.1%
1.0721566821
< 0.1%
1.0734893051
< 0.1%
1.0982303171
< 0.1%
1.1185772181
< 0.1%
1.1188899831
< 0.1%
ValueCountFrequency (%)
7.9900551511
< 0.1%
7.9794213131
< 0.1%
7.8222338581
< 0.1%
7.7479144151
< 0.1%
7.6281881871
< 0.1%
7.3831145021
< 0.1%
7.3258402211
< 0.1%
7.2596285921
< 0.1%
7.2557192731
< 0.1%
7.2445930871
< 0.1%
2026-02-01T22:33:11.139411image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

ATR
Numeric time series

High correlation  Unique 

Distinct2406
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9701532
Minimum0.91395011
Maximum4.0659392
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:33:12.549283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.91395011
5-th percentile1.1511682
Q11.5739803
median1.8745992
Q32.2697704
95-th percentile3.1692183
Maximum4.0659392
Range3.1519891
Interquartile range (IQR)0.69579016

Descriptive statistics

Standard deviation0.58298712
Coefficient of variation (CV)0.29590954
Kurtosis0.71358212
Mean1.9701532
Median Absolute Deviation (MAD)0.34278752
Skewness0.87394998
Sum4740.1885
Variance0.33987398
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.006612618529
2026-02-01T22:33:12.656264image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:12.952487image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 47.03 seconds
2026-02-01T22:33:13.692861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
1.7295918371
 
< 0.1%
1.7489067061
 
< 0.1%
1.6954133691
 
< 0.1%
1.7885981291
 
< 0.1%
1.8751268341
 
< 0.1%
1.9554749171
 
< 0.1%
1.8872267091
 
< 0.1%
2.1095676581
 
< 0.1%
2.244598541
 
< 0.1%
2.1556986441
 
< 0.1%
Other values (2396)2396
99.6%
ValueCountFrequency (%)
0.91395010681
< 0.1%
0.92009652771
< 0.1%
0.93708673431
< 0.1%
0.98425396121
< 0.1%
0.98816145751
< 0.1%
0.98835429851
< 0.1%
0.98900706771
< 0.1%
0.98918613431
< 0.1%
0.98979227721
< 0.1%
0.98995855331
< 0.1%
ValueCountFrequency (%)
4.0659392391
< 0.1%
4.0612292941
< 0.1%
3.9940884121
< 0.1%
3.9854272011
< 0.1%
3.9211081481
< 0.1%
3.9150395441
< 0.1%
3.9074898071
< 0.1%
3.9003736381
< 0.1%
3.8752458461
< 0.1%
3.8702664061
< 0.1%
2026-02-01T22:33:12.745252image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

TRANGE
Real number (ℝ)

High correlation  Zeros 

Distinct10
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9709061
Minimum0
Maximum11
Zeros40
Zeros (%)1.7%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2026-02-01T22:33:14.145380image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median2
Q32
95-th percentile4
Maximum11
Range11
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.0489007
Coefficient of variation (CV)0.53219213
Kurtosis5.2878663
Mean1.9709061
Median Absolute Deviation (MAD)1
Skewness1.5207118
Sum4742
Variance1.1001927
MonotonicityNot monotonic
2026-02-01T22:33:14.197089image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
21002
41.6%
1809
33.6%
3389
 
16.2%
4106
 
4.4%
540
 
1.7%
040
 
1.7%
79
 
0.4%
68
 
0.3%
82
 
0.1%
111
 
< 0.1%
ValueCountFrequency (%)
040
 
1.7%
1809
33.6%
21002
41.6%
3389
 
16.2%
4106
 
4.4%
540
 
1.7%
68
 
0.3%
79
 
0.4%
82
 
0.1%
111
 
< 0.1%
ValueCountFrequency (%)
111
 
< 0.1%
82
 
0.1%
79
 
0.4%
68
 
0.3%
540
 
1.7%
4106
 
4.4%
3389
 
16.2%
21002
41.6%
1809
33.6%
040
 
1.7%

TSF
Numeric time series

High correlation  Non stationary 

Distinct2146
Distinct (%)89.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.059476
Minimum26.307692
Maximum115.1978
Zeros0
Zeros (%)0.0%
Memory size37.6 KiB
2026-02-01T22:33:14.286286image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum26.307692
5-th percentile41.659341
Q151.923077
median73.175824
Q394.002747
95-th percentile105.22802
Maximum115.1978
Range88.89011
Interquartile range (IQR)42.07967

Descriptive statistics

Standard deviation22.247699
Coefficient of variation (CV)0.3045149
Kurtosis-1.3728599
Mean73.059476
Median Absolute Deviation (MAD)21.032967
Skewness-0.023885726
Sum175781.1
Variance494.96012
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.577776729
2026-02-01T22:33:14.374604image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:14.625823image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps499
min3 days
max5 days
mean3 days, 3 hours and 10 minutes
std8 hours, 16 minutes and 47.03 seconds
2026-02-01T22:33:15.448541image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
49.978021985
 
0.2%
51.912087914
 
0.2%
47.846153854
 
0.2%
96.329670333
 
0.1%
52.087912093
 
0.1%
97.120879123
 
0.1%
82.329670333
 
0.1%
48.131868133
 
0.1%
98.582417583
 
0.1%
53.29670333
 
0.1%
Other values (2136)2372
98.6%
ValueCountFrequency (%)
26.307692311
< 0.1%
26.450549451
< 0.1%
26.945054951
< 0.1%
27.208791211
< 0.1%
27.285714291
< 0.1%
27.39560441
< 0.1%
27.417582421
< 0.1%
27.835164841
< 0.1%
27.934065931
< 0.1%
28.09890111
< 0.1%
ValueCountFrequency (%)
115.19780221
< 0.1%
114.54945051
< 0.1%
114.15384621
< 0.1%
113.34065931
< 0.1%
112.54945051
< 0.1%
111.65934071
< 0.1%
111.26373631
< 0.1%
110.90109891
< 0.1%
110.83516481
< 0.1%
110.81318681
< 0.1%
2026-02-01T22:33:14.456594image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

Interactions

2026-02-01T22:32:49.992786image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:35.163413image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:36.048274image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:36.723857image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:37.679636image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:38.577733image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:39.578935image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:40.473783image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:41.416269image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:42.491472image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:43.449175image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:44.425673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:45.498939image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:46.285323image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:47.201033image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:48.167975image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:49.002002image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:50.042421image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:35.212860image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:36.086686image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:36.760981image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:37.739404image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:38.625807image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:39.630679image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:40.533327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:41.465402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:42.544638image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:43.501649image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-02-01T22:32:45.548638image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:46.331914image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-02-01T22:32:48.214890image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-02-01T22:32:35.266816image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:36.124950image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:36.799045image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:37.796775image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:38.674976image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:39.680398image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:40.591499image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:41.515781image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-02-01T22:32:47.315006image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-02-01T22:32:36.836578image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:37.853563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-02-01T22:32:39.729764image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:40.645342image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-02-01T22:32:42.648524image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-02-01T22:32:39.838701image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-02-01T22:32:43.718570image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:44.806067image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:45.738645image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
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2026-02-01T22:32:38.161163image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:39.050344image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:40.060858image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:40.988696image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:42.000973image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:42.989105image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:43.984428image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:45.045137image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:45.940714image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:46.711043image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:47.743455image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:48.613933image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:49.538538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:50.529669image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:35.697404image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:36.443773image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:37.307829image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:38.207243image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:39.104369image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:40.112471image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:41.044068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:42.058759image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:43.040116image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:44.037501image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:45.099486image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:45.984258image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:46.757898image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:47.800783image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:48.659236image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:49.593860image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:50.582495image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:35.751779image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:36.483115image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:37.361666image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:38.255364image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:39.157844image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:40.166352image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:41.097916image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:42.120271image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:43.097925image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:44.092159image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:45.156872image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:46.028143image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:46.804006image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:47.860376image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:48.705879image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:49.650436image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:50.634489image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:35.806266image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:36.522401image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:37.413143image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:38.300752image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:39.210090image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:40.219183image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:41.150848image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:42.179680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:43.148115image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:44.145571image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:45.212391image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:46.068609image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:46.847151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:47.915498image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:48.756646image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:49.704842image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:50.686449image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:35.860682image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:36.562935image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:37.467053image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:38.349789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:39.261955image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:40.272324image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:41.203439image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:42.243440image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:43.220788image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:44.202872image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:45.270927image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:46.115029image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:46.889677image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:47.969600image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:48.807106image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:49.765835image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:50.738328image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:35.914288image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:36.605149image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:37.523965image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:38.398708image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:39.313282image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:40.325991image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:41.259672image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:42.307330image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:43.281068image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:44.260307image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:45.333686image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:46.159226image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:46.935928image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:48.024700image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:48.860151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:49.823893image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:50.794804image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:35.963582image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:36.646390image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:37.578396image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:38.449777image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:39.474788image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:40.378211image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:41.313401image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:42.371736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:43.339362image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:44.319450image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:45.391680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:46.204083image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:47.090338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:48.074971image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:48.909736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:49.883049image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:50.846207image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:36.008026image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:36.685907image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:37.631865image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:38.519519image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:39.528771image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:40.428563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:41.367639image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:42.432582image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:43.397513image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:44.373842image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:45.448510image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:46.245115image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:47.147751image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:48.123414image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:48.958054image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:32:49.938030image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2026-02-01T22:33:15.886556image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ADATRBOPCMOEMAKAMAMAMFIMidPriceNATROBVROCTRANGETSFWILLRWMAclose
AD1.000-0.4340.0230.007-0.215-0.212-0.2160.018-0.215-0.1370.556-0.027-0.251-0.222-0.033-0.216-0.218
ATR-0.4341.0000.000-0.1370.2960.2940.295-0.1130.2940.504-0.315-0.0540.5880.286-0.0700.2930.290
BOP0.0230.0001.0000.3560.0120.0080.0070.1470.009-0.0540.0800.265-0.0490.0190.4350.0130.061
CMO0.007-0.1370.3561.0000.0550.0390.0440.7960.040-0.2330.2200.862-0.1700.1300.9180.0720.139
EMA-0.2150.2960.0120.0551.0000.9981.0000.0530.999-0.6240.2530.0060.1700.9940.0361.0000.994
KAMA-0.2120.2940.0080.0390.9981.0000.9980.0420.998-0.6250.256-0.0100.1710.9910.0180.9980.991
MA-0.2160.2950.0070.0441.0000.9981.0000.0480.999-0.6230.251-0.0060.1700.9930.0230.9990.992
MFI0.018-0.1130.1470.7960.0530.0420.0481.0000.042-0.2100.2010.737-0.1110.1310.7420.0720.114
MidPrice-0.2150.2940.0090.0400.9990.9980.9990.0421.000-0.6240.248-0.0140.1690.9920.0160.9980.992
NATR-0.1370.504-0.054-0.233-0.624-0.625-0.623-0.210-0.6241.000-0.458-0.1290.323-0.633-0.168-0.627-0.632
OBV0.556-0.3150.0800.2200.2530.2560.2510.2010.248-0.4581.0000.127-0.1750.2580.1650.2550.260
ROC-0.027-0.0540.2650.8620.006-0.010-0.0060.737-0.014-0.1290.1271.000-0.1060.0880.8640.0240.085
TRANGE-0.2510.588-0.049-0.1700.1700.1710.170-0.1110.1690.323-0.175-0.1061.0000.159-0.1300.1670.157
TSF-0.2220.2860.0190.1300.9940.9910.9930.1310.992-0.6330.2580.0880.1591.0000.1060.9970.996
WILLR-0.033-0.0700.4350.9180.0360.0180.0230.7420.016-0.1680.1650.864-0.1300.1061.0000.0510.122
WMA-0.2160.2930.0130.0721.0000.9980.9990.0720.998-0.6270.2550.0240.1670.9970.0511.0000.996
close-0.2180.2900.0610.1390.9940.9910.9920.1140.992-0.6320.2600.0850.1570.9960.1220.9961.000

Missing values

2026-02-01T22:32:50.960539image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2026-02-01T22:32:51.051330image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Datecloserepaired?MAEMAKAMAWMAMidPriceBOPCMOMFIROCWILLRADOBVNATRATRTRANGETSF
2010-01-262010-01-2675False77.677.53057075.86234376.54545578.00.000000-66.53276722.279956-9.638554-90.0000001.256939e+06-1370963.02.3061221.7295921.073.670330
2010-01-272010-01-2774False76.976.88864875.33355875.89090977.0-0.500000-71.08503210.101811-8.641975-90.9090911.256939e+06-1727142.02.3633871.7489072.072.879121
2010-01-282010-01-2874False76.376.36343974.97831375.36363676.50.000000-71.0850329.279363-7.500000-90.9090911.549850e+06-1727142.02.2910991.6954131.072.384615
2010-01-292010-01-2973False75.775.75190574.45131274.76363675.5-0.333333-75.2425048.491612-7.594937-91.6666671.438093e+06-2062412.02.4501341.7885983.071.901099
2010-02-012010-02-0174False75.375.43337774.39099174.45454575.50.333333-51.1025747.158936-5.128205-80.0000001.530563e+06-1785001.02.5339551.8751273.072.032967
2010-02-022010-02-0277False75.175.71821774.48023274.76363675.50.666667-3.55364916.863484-2.531646-44.4444441.896832e+06-1418732.02.5395781.9554753.072.967033
2010-02-032010-02-0377False75.075.95126974.52375375.10909175.00.000000-3.55364927.601955-1.282051-37.5000001.505538e+06-1418732.02.4509441.8872271.073.857143
2010-02-042010-02-0473False74.775.41467474.44402874.74545575.0-0.800000-36.46449526.052691-3.947368-85.7142861.191203e+06-1942624.02.8898192.1095685.073.527473
2010-02-052010-02-0571False74.374.61200674.20174574.07272774.0-0.500000-46.58973823.909991-5.333333-88.8888898.931321e+05-2538766.03.1614062.2445994.072.648352
2010-02-082010-02-0872False74.074.13709674.11059073.65454574.00.000000-34.66695823.909991-4.000000-77.7777781.238770e+06-2193128.02.9940262.1556991.072.461538
Datecloserepaired?MAEMAKAMAWMAMidPriceBOPCMOMFIROCWILLRADOBVNATRATRTRANGETSF
2019-08-062019-08-0654False56.155.87701956.85092755.80000056.0-0.500000-21.33492946.668222-5.263158-83.3333334.015743e+0713996760.03.3855601.8282022.055.692308
2019-08-072019-08-0751False55.654.99028856.43932354.87272755.0-0.666667-37.95582341.494913-8.928571-100.0000003.909421e+0712933546.03.7488281.9119023.054.054945
2019-08-082019-08-0853False55.354.62841856.33901454.40000055.01.000000-19.28644846.703307-5.357143-75.0000003.981897e+0713658308.03.6192351.9181952.053.296703
2019-08-092019-08-0954False55.154.51416056.29861654.16363655.00.333333-10.94529447.206311-3.571429-62.5000004.006110e+0714384694.03.6953081.9954673.052.923077
2019-08-122019-08-1255False54.954.60249556.27618654.14545555.01.000000-2.94684947.669328-3.508772-50.0000004.067213e+0714995721.03.4988401.9243621.053.076923
2019-08-132019-08-1357False54.855.03840556.28288654.52727355.00.66666711.26862657.467634-1.724138-25.0000004.145562e+0715779207.03.5108652.0011933.053.692308
2019-08-142019-08-1455False54.455.03142256.23900554.56363654.5-0.666667-3.53226652.692417-6.779661-50.0000004.121619e+0715060914.03.7682482.0725363.053.703297
2019-08-152019-08-1554False54.454.84389156.22968554.49090954.0-1.000000-10.17062949.7116400.000000-62.5000004.068832e+0714533048.03.6961611.9959271.053.461538
2019-08-162019-08-1655False54.354.87227456.21621654.60000054.00.000000-2.34527147.564612-1.785714-50.0000004.068832e+0714701393.03.6294871.9962182.053.747253
2019-08-192019-08-1956False54.455.07731556.21384854.90909154.01.0000005.14114244.6931931.818182-37.5000004.080189e+0714814964.03.4376061.9250591.054.560440